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Record W4289262439 · doi:10.2118/209347-pa

Reinjection of Produced (Sheared) Polymer in a Canadian Viscous Oil Reservoir: Considerations to Improve Economics and Reduce Carbon Footprint

2022· article· en· W4289262439 on OpenAlexaboutno aff
Pinaki Ghosh, Ryan R. Wilton, Annalise Bowers, Thomas O’Brien, Yu Cao, Clayton Wilson, Mahmoud Ould Metidji, Guillaume Dupuis, Ravi Ravikiran

Bibliographic record

VenueSPE Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsEnhanced oil recoveryResidual oilPetroleum engineeringPolymerAsphaltProduced waterEnvironmental scienceOil fieldMaterials scienceProcess engineeringWaste managementGeologyEngineeringComposite material

Abstract

fetched live from OpenAlex

Summary Chemical enhanced oil recovery (EOR) flooding is one of the more attractive methods to improve oil recovery. However, during times of instability in the oil market, cost of specialized chemicals and necessary facilities for alkali-surfactant-polymer (ASP) or surfactant-polymer makes this technology very expensive and challenging to implement in the field. In the majority of cases, polymer flooding alone has proved to be the most cost-effective solution that has resulted in attractive and predictable return on investment. In recent times, a challenging economic environment has operators looking for added economic and sustainable savings. The possibility of reinjection of produced (sheared) polymer to offset injection concentration requirements can lead to reduced cost and longer sustainability of oil recovery, thus offering a subsequent reduction in produced water (PW) treatment and a reduced full-cycle carbon footprint. This innovative approach is subject to conditions experienced in the surface facilities, as well as in the reservoir. As part of this study, different polymer chemistries were investigated for their mobility control in porous media and comparative effect on oil recovery trends in the presence of produced fluid containing residual polymer. The initial fluid-fluid testing and laboratory characterization results were validated against a mature field EOR project for reduction in polymer requirement to achieve target viscosity. Monophasic flow behavior experiments were performed in Bentheimer and Berea outcrop cores, while oil recovery experiments were performed in Bentheimer outcrops with different polymer solutions—freshly made and combinations with residual produced polymer. Based on field observations and laboratory measurements, a 10 to 15% reduction in fresh polymer loading could be achieved through the reutilization of water containing residual polymer in these specific field conditions. Note, this case study involved produced polymer that was degraded through progressive cavity pumps (PCPs) resulting in only 15 to 20% of the injected viscosity in the produced fluids in addition to thermal and chemical degradations. The monophasic injectivity experiments in both outcrop cores resulted in similar resistance factors (RFs) for fresh polymer and blends with produced water reinjection containing residual polymer (PWcRP) solution, establishing the robustness of this blending system. Oil recovery experiments also resulted in similar oil displacement behavior [approximately 30 to 40% oil originally in place (OOIP) after 0.5 pore volumes (PV) waterflood] for fresh and blends with sheared polymer solutions, validating no loss in recovery potential, with the added benefit of 10 to 15% polymer loading reduction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.223
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractyes

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